Search

Rotor dynamics plays a crucial role in the performance and safety of rotating machinery, with disk position and unbalance significantly impacting system behavior. This study investigates the dynamic characteristics of two rotor configurations: a centrally mounted unbalanced disk (Rotor05un) and an off-center unbalanced disk (Rotor025un). Using numerical simulations and Monte Carlo analysis, we examined critical speeds and orbital patterns for both configurations. Probability distributions of shaft orbital positions revealed distinct patterns for each configuration. Quantile analysis revealed approximate linear trends for Rotor025un, suggesting higher system stiffness and more predictable behavior near critical speeds. Cross-sectional analyses of the orbits provided insights into the complex interactions between disk position, gyroscopic effects, and system natural frequencies. These findings provide valuable insights for rotor system design, particularly for applications with non-ideal mass distributions. The study goes beyond traditional critical speed analysis to examine orbital patterns and point on orbit occurrence from a probabilistic perspective. Based on the simulation of the orbits, an orbital is determined that allows the probability of the shaft occurring at the analyzed distance from the origin to be determined. The paper also offers insights into the complex interaction behavior of chosen rotor configurations and highlights the importance of considering disk position in predicting and optimizing rotor dynamic behavior, contributing to the development of more robust and efficient rotating machinery. [ABSTRACT FROM AUTHOR]

The proposed work focuses on the design of a current-reused biomedical amplifier; it is a microwatt-level electrocardiogram (ECG) analog circuit design that addresses low power consumption and noise efficiency. As implantable devices require unobtrusiveness and longevity, the current reuse technique in this circuit effectively enhances power and noise efficiencies. Using 90 nm technology enables efficient circuit implementation, yielding promising simulation results. At 100 Hz, the noise performance reaches 62.095 nV/vHz, while the power consumption is only 8.3797 µW. These advancements are pivotal for next-generation implantable devices, ensuring reliable operation and reducing frequent battery replacements, improving patient convenience. Moreover, the high noise efficiency ensures that ECG signals are captured with high fidelity, crucial for accurate monitoring and diagnosis. This research addresses the challenges in implantable ECG analog circuit design and sets a benchmark for future developments. The techniques employed can be adapted for other bio signal monitoring devices, broadening the impact on healthcare technology. Ultimately, this advancement contributes to more efficient, reliable, and long-lasting medical devices, enhancing patient monitoring and healthcare on a broader scale. [ABSTRACT FROM AUTHOR]

Abstract Parking difficulties have become a social issue that people have to solve. Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents. The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method (RF-LNMPC) in order to improve the overall path tracking accuracy in parking conditions. Firstly, A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively. Secondly, the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization, of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution. Thirdly, the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented. The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically. Finally, the proposed RF-LNMPC is implemented on a self-driving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions. The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.

The paper introduces a new approach for designing fractional-order inverse Chebyshev low-pass filters (FOICLF), with an emphasis on filters with an order of 1+α. The coefficients for these filters are determined through Gray Wolf Optimization by approximating filter response with the ideal response of same order FOICLF. Stability tests are conducted, and filters are implemented using Multiple Input Single Output topology with commercial ICs. Comparative analysis reveals close proximity between the ideal response of FOICLF and the designed filters, featuring maximum and mean square errors of –22.48 dB and –61.07 dB, respectively, for 1.7 order. Results are benchmarked against existing literature, highlighting superior performance in stopband and passband magnitude errors and stopband attenuation. Process, Voltage, and Temperature analysis assesses the impact of the parameter variations on the –3 dB frequency, assuring the robustness of designed filters with relative standard deviations ranging from 0.003% to 3.013% for the 1.7 order filter. [ABSTRACT FROM AUTHOR]

A metabolic coupling between glutamate and N-acetylaspartate measured by in vivo magnetic resonance spectroscopy has been recently reported in the literature with inconsistent findings. In this study, confounders originating from Pearson's spurious correlation of ratios and spectral correlation due to overlapping magnetic resonance spectroscopy signals of glutamate and N-acetylaspartate were practically eliminated to facilitate the determination of any metabolic link between glutamate and N-acetylaspartate in the human brain using in vivo magnetic resonance spectroscopy. In both occipital and medial prefrontal cortices of healthy individuals, correlations between glutamate and N-acetylaspartate were found to be insignificant. Our results do not lend support to a recent hypothesis that N-acetylaspartate serves as a significant reservoir for the rapid replenishment of glutamate during signaling or stress. [ABSTRACT FROM AUTHOR]

This research examines the coal transportation system at Site Port S, a PT BCX coal mining concession. The site serves as a transit terminal for coal hauled from Site B using trucks, where the coal is dumped via two inloading conveyors. Currently, the daily haul truck capacity is 50,000 tons, while the conveyors handle 54,000 tons daily. However, when one of the conveyors is under maintenance or experiencing technical issues, production opportunities are lost, jeopardizing the achievement of future coal production targets, especially as peak production is expected over the next three years. To address this, the research aims to assess the feasibility of building a new inloading conveyor to serve as a backup system. The research uses capital expenditure (CAPEX) calculations, including previous inloading conveyor costs and inflation rates, as well as operating expenses (OPEX) and cost per ton to operate the plant. A discounted cash flow (DCF) analysis was conducted to determine the net present value (NPV) of building or renting a new conveyor unit. With a weighted average cost of capital (WACC) of 11.9%, the NPV results show a positive $4.8 million for building a new unit, compared to a negative $22.3 million for renting. The results indicate that building a new conveyor unit is significantly more profitable than renting. Additionally, owning the unit provides flexibility, as it could potentially be used at other sites in the future. The findings have important implications for optimizing coal transportation systems and ensuring long-term production efficiency. [ABSTRACT FROM AUTHOR]

With increasing contamination of waterbodies, access to clean drinking water has become a challenge. Preventing further contamination and cleaning up of existing contamination are the immediate steps to address this challenge. For this, the sources of contamination and their relative contributions need to be ascertained. The bottom sediments from an urban waterbody named "Conolly Canal" was analyzed for heavy metal contamination. The level of contamination of the waterbody was assessed using Pollution Load Index. A Monte Carlo analysis (MCA) was performed on the heavy metals concentrations measured to apportion the contribution among the identified sources. The results of MCA were used to proportion the concentration of chemicals among the responsible parties based on the concentration of the contaminants in the waterbody. The study presents a robust procedure for source apportionment, which can be adopted in similar situations. [ABSTRACT FROM AUTHOR]

Parking difficulties have become a social issue that people have to solve. Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents. The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method (RF-LNMPC) in order to improve the overall path tracking accuracy in parking conditions. Firstly, A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively. Secondly, the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization, of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution. Thirdly, the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented. The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically. Finally, the proposed RF-LNMPC is implemented on a self-driving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions. The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future. [ABSTRACT FROM AUTHOR]

The seabed of the Gunneklev Fjord in south-eastern Norway is covered with exceptionally soft contaminated sediment containing mercury and dioxins. The sediments have an undrained shear strength less than 1 kPa and a variable thickness of up to 2.5 m. To reduce the potential for leaching of contaminants from these sediments, Hydro Energy AS developed a remediation plan involving capping of the sediment. Significant uncertainties are associated with the sediment's undrained shear strength and the cap thickness. An unfortunate combination of low shear strength and thick cap could cause slope failure (e.g. translational sliding of the sediment and/or bearing capacity failure (e.g. punching through). Failure, particularly slope failure, can cause spreading of the contaminants in the fjord causing serious consequences. This paper presents an assessment of the probability of slope failure associated with the contaminated sediment before and after the cap placement. Probability of bearing capacity failure is considered to have more local effect and is also discussed briefly. The study used the Monte Carlo method with random undrained shear strength and sediment thickness. The simulations show high slope failure probability when the seabed inclination was ≥ 1:50 combined with an average undrained shear strength ≤ 0.4 kPa. Based on the probabilistic analyses, a pilot field testing campaign was carried out (after this study) with 20-cm thickness cap in the "gentle" sloping area and 5-cm thickness in the "steep" areas to avoid causing a failure. The analyses were used to support evidence-based decision-making on the cap design and implementation for further field testing. [ABSTRACT FROM AUTHOR]

One technique, especially in chaos-based cryptographic applications, is to include the message in the evolution of the dynamical system. This paper aims to find out if and to what extent the statistical behavior of the chaotic system is affected by the message inclusion in its dynamic evolution. The study is illustrated by the dynamical system described by the logistic map in cryptographic applications based on images. The evaluation of the statistical behavior was performed on an original scheme proposed. The Monte Carlo analysis of the applied Kolmogorov–Smirnov statistical test revealed that the dynamical system in the processing scheme with message inclusion does not modify its proper statistical behavior (revealed by definition relation). This was possible due to the proposed scheme designed. Namely, this scheme contains a decision switch which, supported by an appropriate choice of the magnitude of the scaling factor, ensures that the values of the dynamical system are maintained in the definition domain. The proposed framework for analyzing the statistical properties and for preserving the dynamical system behavior is one main contribution of this research. The message inclusion scheme also provides an enhancement with cryptographic mixing functions applied internally; the statistical behavior of the dynamical system is also analyzed in this case. Thus, the paper contributes to the theoretical complex characterization of the dynamical system considering also the message inclusion case. [ABSTRACT FROM AUTHOR]

A variable threshold voltage hybrid evaluation network based dynamic XOR/XNOR gate is presented to reduce the parameters leakage power dissipation, dynamic power, and layout area compared to existing dynamic gates under similar delay time conditions. This study explores the impacts of process, supply voltage, and temperature changes on leakage power dissipation and dynamic power using Monte Carlo simulation. The Monte Carlo analysis demonstrates that leakage power dissipation and dynamic power reduction have significantly improved. Furthermore, when compared to hybrid type dynamic XOR/XNOR (N-type XOR/XNOR), the proposed design reduces leakage power and dynamic power consumption by 6.1% (54.0%) and 18.75% (35.0%), respectively. While the proposed design has a slight layout area penalty compared to a hybrid type dynamic XOR/XNOR, it offers the same amount of the layout area as a traditional N-type XOR/XNOR. [ABSTRACT FROM AUTHOR]

Successful management of large space systems, such as the most recent Proliferated Low Earth Orbit (P-LEO) constellations, demands an increased level of autonomy and irregular behavior detection capability. Existing techniques for satellite network management rely on monitoring satellites individually, potentially failing to capture events shared across multiple units. In this work, we propose a pipeline for identifying anomalous connections in proliferated satellite networks. Our pipeline relies on representing a satellite constellation as a dynamic graph. Dynamic graphs can be conveniently exploited to represent P-LEO networks, as they allow to capture meaningful structural and temporal correlations. Such spatial and temporal information are first projected into an embedding space; next, this encoded representation is processed by a transformer-encoder network for the anomaly detection task. We conduct extensive analyses of the main problem parameters, including the temporal horizon, the structure of the graph, and the size of the constellation. To assess the general performance of the method, we perform a Monte Carlo analysis on 960 ground node pair connections, providing empirical evidence of the algorithm's generalization capability. The obtained results encourage the extension of the method to more complex, realistic modeling and kindred applications such as the on-edge detection problem. • Topology changes of P-LEO satellite networks are explored to detect anomalous links. • Spatial–temporal features of the network are leveraged to boost performance. • Evidence of algorithm generalization capability is collected via randomized simulations. [ABSTRACT FROM AUTHOR]

Transistor random threshold voltage variations due to process fluctuations seriously affects the stability of Static Random Access Memory (SRAM). In this paper, a SRAM bit transistors threshold voltage $({Vth})$ deviation monitoring scheme and system is proposed. This scheme ingeniously achieves on-chip measurement of all transistors threshold voltages without altering compact SRAM bit array layout. Control signal strategies and Transistor ${Vth}$ Determination Circuit (TVDC) for different types of Devices Under Test (DUTs) have been proposed. The system is implemented using a 65 nm CMOS process with a core area of 0.01875mm2. Through Monte Carlo analysis, the Weighted Average (WA) difference of the proposed scheme and the direct measurement method is not more than 10mV, and the Root Mean Square Error (RMSE) difference is not more than 3mV. This system can also effectively detect the cell position of the transistor threshold voltage mismatch simulated by modifying the substrate voltage. For SRAM arrays of different scales, the method proposed in this paper has area efficiency and flexible reconfigurability. [ABSTRACT FROM AUTHOR]

Purpose: Potentially contradictory indicators in Life Cycle Assessment cause ambiguity and thus uncertainty regarding the interpretation of results. The weighting-based ecological scarcity method (ESM) aims at reducing interpretation uncertainty by applying policy-based normative target values. However, the definition of these target values is uncertain due to different reasons such as questionable temporal representativeness. By means of an uncertainty analysis, this paper examines if ESMs are an appropriate approach to support robust decisions on multidimensional environmental impacts. Methods: To assess the effect of uncertain target values (inputs) on environmental indicators (output), the ESM based Life Cycle Impact Assessment (LCIA) is combined with a Monte Carlo Analysis. The comprehensive uncertainty analysis includes the following steps: (1) sample generation, (2) output calculation and (3) results analysis and visualisation. (1) To generate a sample, moderate and strict limits for target values are derived from laws, directives or strategies. Random input parameters are drawn from a uniform distribution within those limits. (2) The sample is used to conduct several LCIAs leading to a distribution of total impact scores. (3) The results' robustness is evaluated by means of the rank acceptability index to identify stable ranks for energy generation systems taken from ecoinvent v. 3.7.1. Results and discussion: Applying moderate and strict target values in the ESM, results in substantial differences in the weighting sets. Even though the application of stricter target values changes the contribution of an environmental indicator to the total impact score the ranking of the energy generation systems varies only slightly. Moreover, the Monte Carlo Analysis reveals that displacement effects in ranks are not arbitrary: systems switch at most between ranks next to each other and most of the analysed systems dominate at least a single rank. Technologies with high shares of land use, global warming and air pollutants and particulate matter show a higher rank variance. Conclusions: The weighting schemes, deduced from target values, provide a meaningful ranking of alternatives. At the same time, the results are not excessively sensitive to the uncertainties of the target values, i.e. the inherent uncertainty of the target values does not result in arbitrary outcomes, which is necessary to support robust decisions. The ESM is able to effectively facilitate decision making by making different environmental issues comparable. [ABSTRACT FROM AUTHOR]

Human examiners, known as panelists, are exposed to an unknown occupational exposure risk while determining odor concentration (Cod) using dynamic olfactometry. In the literature, a few papers, based on a deterministic approach, have been proposed to establish this occupational risk. As a result, the purpose of this study is to develop and apply a probabilistic approach, based on the randomization of exposure parameters, for assessing and evaluating the occupational exposure risk among olfactometric examiners. In this methodology, the risk is assessed by computing the hazard index (HI) and inhalation risk (IR) to determine the non-carcinogenic and carcinogenic risks. To randomize the exposure parameters, a Monte Carlo simulation was described and then applied in real exposure scenario to establish the exposure risk in terms of probability. Therefore, a one-year survey of the working activity of olfactometric examiners of Laboratorio Olfattometrico of Politecnico di Milano university was conducted. Based on this data collection (exposure parameters and chemical data, divided according to sample categories), a randomized exposure scenario was constructed to estimate the probability and cumulative distribution function of risk parameters. Different distributions were obtained for different industrial samples categories and were compared with respect to acceptability criteria (the value of HI and IR at 95th percentile of distribution). The elaboration provided evidence that negligible non-carcinogenic and carcinogenic risks are associated with the panelists’ activity, according to an entire annual dataset. The application of probabilistic risk assessment provides a more comprehensive and effective characterization of the general exposure scenario for olfactometric examiners, surpassing the limitations of a deterministic approach. This method can be extended to future exposure scenarios and enables the selection of the most effective risk management strategies to protect the health of olfactometric examiners.

Copyright of Acta Prataculturae Sinica is the property of Acta Prataculturae Sinica Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

ABSTRACT This study aimed to analyze the economic viability of the implementation of a mechanized harvesting of broilers where the activity is carried out entirely manually. The viability indicators used were net present value (NPV), net future value (NFV), net uniform value (NUV), discounted payback (DP), and internal rate of return (IRR). Scenario analysis, sensitivity, and Monte Carlo simulation were performed in the present study. The results showed that the initial investment was US$ 1,868,302.76. The average price paid by the slaughterhouse to third-party manual harvesting companies was US$ 18.17 per thousand broilers, which was converted into revenue in the cash flow of the project. The cash flow result was positive at US$ 22,256.14 over the entire study period considering a daily catch of 144 thousand broilers. The results of the economic viability analysis were NPV of US$ 64,786.23, NFV of US$ 333,382.11, NUV of US$ 735.19, DP of 13.82 years, IRR of 0.965 monthly, and modified IRR of 0.933 monthly. These values prove the economic viability of implementing the project considering the market conditions at the time of the study. The analysis of scenarios showed great sensitivity to the exchange rate and the price of fuels. The Monte Carlo simulation highlighted a moderate risk of negative NPV, emphasizing the importance of considering this variable when making decisions. Despite these challenges, the potential benefits of mechanized harvesting, such as increased efficiency and reduced labor costs, make it a promising alternative to manual harvesting, even for small to medium-sized poultry industries.

Rotor dynamics plays a crucial role in the performance and safety of rotating machinery, with disk position and unbalance significantly impacting system behavior. This study investigates the dynamic characteristics of two rotor configurations: a centrally mounted unbalanced disk (Rotor05un) and an off-center unbalanced disk (Rotor025un). Using numerical simulations and Monte Carlo analysis, we examined critical speeds and orbital patterns for both configurations. Probability distributions of shaft orbital positions revealed distinct patterns for each configuration. Quantile analysis revealed approximate linear trends for Rotor025un, suggesting higher system stiffness and more predictable behavior near critical speeds. Cross-sectional analyses of the orbits provided insights into the complex interactions between disk position, gyroscopic effects, and system natural frequencies. These findings provide valuable insights for rotor system design, particularly for applications with non-ideal mass distributions. The study goes beyond traditional critical speed analysis to examine orbital patterns and point on orbit occurrence from a probabilistic perspective. Based on the simulation of the orbits, an orbital is determined that allows the probability of the shaft occurring at the analyzed distance from the origin to be determined. The paper also offers insights into the complex interaction behavior of chosen rotor configurations and highlights the importance of considering disk position in predicting and optimizing rotor dynamic behavior, contributing to the development of more robust and efficient rotating machinery.

This work presents an estimate of the slip activation potential of existing fractures in a remote northern community located on Canadian Shield rocks for geothermal purposes. To accomplish this objective, we analyzed outcrop analogues and recorded geometrical properties of fractures, namely the strike and dip. Then, we estimated the stress regime in the study area through an empirical approach and performed a probabilistic slip tendency analysis. This allowed us to determine the slip probability of the pre-existing fractures at the current state of stress, the orientation of fractures that are most likely to be activated and the fluid pressures needed for the slip activation of pre-existing fractures, which are key aspects for developing Enhanced Geothermal Systems. The results of this simple, yet effective, analysis suggest that at the current state of stress, the pre-existing natural fractures are relatively stable, and an injection pressure of about 12.5 MPa/km could be required to activate the most optimally oriented fractures to slip. An injection of water at this pressure gradient could open the optimally oriented pre-existing fractures and enhance the permeability of the reservoir for geothermal fluid extraction. The information described in this paper provides a significant contribution to the geothermal research underway in remote northern communities. [ABSTRACT FROM AUTHOR]

The Carbon Border Adjustment Mechanism was developed to ensure that industrial sectors operating outside the EU follow the same environmental standards and targets while competing with the EU's carbon market. This mechanism aims to calculate the carbon footprint of goods and services imported into the EU and make carbon adjustments accordingly. The transition phase, starting in 2023, represents the period when the Carbon Border Adjustment Mechanism will be implemented. The completion of the transition phase is targeted for 2025. By this date, the effective implementation of this mechanism is aimed at demonstrating that countries outside of the EU comply with emissions regulations using Carbon at Border certificates. The textile industry's products have a significant environmental impact throughout their life cycle, from the production of raw materials to the disposal of the finished product. Textile production, especially synthetic yarns, requires large amounts of energy, contributing to greenhouse gas emissions and climate change. In this study, a "cradle-to-customer plus waste" life cycle assessment (LCA) is conducted to evaluate the environmental impacts of two products in the textile sector. The Monte Carlo analysis method can be used to handle uncertainties in LCA calculations. It is a method for modeling uncertainties and statistically evaluating results. In this study, this method is preferred at the stage of determining uncertainties. The processes from chips to yarns are investigated for two synthetic yarns: polyester (PES) and polypropylene (PP). The carbon emissions of PP and PES used in textiles are calculated for the first time in this study using detailed modeling with LCAs and a real application. The main production operations are considered: (i) transport of raw materials and packaging material, (ii) energy consumption during the production process, (iii) transport of products, and (iv) end-of-life steps. When the actual data obtained from a company are analyzed, the carbon footprints (CFs) of the PES and PP are calculated to be 13.40 t CO2-eq (t PES)-1 and 6.42 t CO2-eq (t PP)-1, respectively. These data can be used as reference points for future studies and comparisons. According to the results obtained, when the energy consumption and raw material stages in the production of the PES and PP products are compared, it is seen that the CF of PP yarn is lower, and it is more environmentally friendly. These findings can be utilized to enhance government policies aimed at reducing greenhouse gas emissions and managing synthetic yarn production in Türkiye. Since PP and PES raw materials are predominantly used in synthetic yarns, this study's objective is to quantify the carbon emissions associated with the utilization of these raw materials and provide guidance to companies engaged in their production. [ABSTRACT FROM AUTHOR]

Twenty-seven scientists met for the annual Auxological conference held at Aschau, Germany, to particularly discuss the interaction between social factors and human growth, and to highlight several topics of general interest to the regulation of human growth. Humans are social mammals. Humans show and share personal interests and needs, and are able to strategically adjust size according to social position, with love and hope being prime factors in the regulation of growth. In contrast to Western societies, where body size has been shown to be an important predictor of socioeconomic status, egalitarian societies without formalized hierarchy and material wealth-dependent social status do not appear to similarly integrate body size and social network. Social network structures can be modeled by Monte Carlo simulation. Modeling dominance hierarchies suggests that winner-loser effects play a pivotal role in robust self-organization that transcends the specifics of the individual. Further improvements of the St. Nicolas House analysis using re-sampling/bootstrap techniques yielded encouraging results for exploring dense networks of interacting variables. Customized pediatric growth references, and approaches towards a Digital Rare Disease Growth Chart Library were presented. First attempts with a mobile phone application were presented to investigate the associations between maternal pre-pregnancy overweight, gestational weight gain, and the child’s future motor development. Clinical contributions included growth patterns of individuals with Silver-Russell syndrome, and treatment burden in children with growth hormone deficiency. Contributions on sports highlighted the fallacy inherent in disregarding the biological maturation status when interpreting physical performance outcomes. The meeting explored the complex influence of nutrition and lifestyle on menarcheal age of Lithuanian girls and emphasized regional trends in height of Austrian recruits. Examples of the psychosocial stress caused by the forced migration of modern Kyrgyz children and Polish children after World War II were presented, as well as the effects of nutritional stress during and after World War I. The session concluded with a discussion of recent trends in gun violence affecting children and adolescents in the United States, and aspects of life history theory using the example of "Borderline Personality Disorder." The features of this disorder are consistent with the notion that it reflects a "fast" life history strategy, with higher levels of allostatic load, higher levels of aggression, and greater exposure to both childhood adversity and chronic stress. The results were discussed in light of evolutionary guided research. In all contributions presented here, written informed consent was obtained from all participants in accordance with institutional Human investigation committee guidelines in accordance with the Declaration of Helsinki amended October 2013, after information about the procedures used.

This research paper presents a symmetrical current-tunable active-RC all-pass filter that uses an active BJT coupled with R and C. The circuit's symmetrical structure ensures that the differential signals are treated equally, resulting in improved performance. Furthermore, the filter's ability to adjust the frequency by bias current makes it suitable for a wide range of applications, such as improving phase properties and creating other types of filters. The simulation results obtained through the Pspice program show that the value of the operating frequency can be adjusted by bias current, which is the highlight of this research. The transfer function of the circuit shows a response of about 0 dB and -90° respectively, indicating that the circuit can change the phase of the input signal without changing its magnitude. This feature is particularly useful in signal processing applications where phase changes are required. In addition, the paper discusses how the operating frequency can be increased by decreasing the capacitor. The transfer function of the circuit analyzed shows that the operating frequency (f0) is inversely proportional to the product of the capacitors. Therefore, decreasing the value of C increases the operating frequency of the circuit. Monte Carlo analysis results are also presented for resistors, capacitors, and transistors with error values. This analysis helps determine the effect of errors on the output signal of the circuit. The results show that the output signal is sensitive to changes in the resistor values, which can affect the accuracy of the filter. Therefore, it is important to select high-quality resistors to ensure that the filter operates accurately. [ABSTRACT FROM AUTHOR]

Statistical and sensitivity analyses were carried out on the use of the Michaëlis-Menten kinetic model to estimate respiration rates of fresh produce during modified atmosphere packaging (MAP). Monte Carlo simulation, which is used to explain the effects of risk and uncertainty in predictive and forecasting models, showed that the carbon dioxide concentration term was the most sensitive in the experimental cases tested. This term was modified by adding an exponential term and reintroduced back into the Michaëlis-Menten model, improving its stability and predictive accuracy. The analysis, was based on the respiration rates of fresh-cut ' Romaine ' lettuce (Lactuca sativa var. longifolia) treated with two disinfection methods, a chlorine solution (sodium hypochlorite, 100 ppm) and an organic acids solution (ascorbic and citric acid, 1% w/v each) and stored at 4.18 °C for 7 d. Respiration rates were significantly influenced by disinfection methods, storage time and their interaction in both cases. • Monte Carlo showed that carbon dioxide term affects most the respiration rate. • Exponential term in inhibition models improved prediction stability. • At high oxygen, respiration is controlled from carbon dioxide concentration. • Exponential term resulted in positive and significant inhibition parameters. [ABSTRACT FROM AUTHOR]

Neurochemical concentrations determined by magnetic resonance spectroscopy (MRS) have been treated as statistically independent measurements in various clinical MRS studies. However, spectral overlap, independent of any biological effects, could lead to significant correlations between neurochemical concentrations extracted from spectral fitting of MRS data, confounding determination of correlations of biological origin. Short echo time (TE) proton MRS spectra are very crowded because of the comparatively narrow chemical shift dispersion of proton nuclear spins. In this study, the complex neurochemical correlations of spectral origin in short‐TE MRS spectra were quantified. The effects of macromolecules and the background spectral baseline on metabolite–metabolite correlations were also analyzed. Our results demonstrate the importance of factoring in spectral correlations when correlating overlapping metabolite signals in short‐TE spectra with clinical parameters. [ABSTRACT FROM AUTHOR]

The current deployment of 5G NR in the frequency band 4800–4990 MHz in multiple countries near the coastlines indicated that there might be a potential risk of harmful interference impacting aeronautical and maritime systems located in international airspace and international waters. This raised numerous concerns about whether 5G NR system rollouts in that band need to be restricted by the power flux density limits created at the border of the territorial waters, which equals 12 nautical miles from the coastline. This work contains a case study based on the example of the Pacific region, where a simulation of aggregate interference from 5G NR base stations and user equipment deployed in the cities near the coastline using Monte Carlo analysis was conducted. The results of the study show that no harmful interference to the aeronautical and maritime services operating in international airspace and waters is expected even when the aircraft or vessels are located at the border of the territorial airspace and waters from the coastline. Therefore, no restriction to the 5G NR deployment in the coastline regions in the frequency band 4800–4990 MHz is required.

The eye diagram performance of the Si ring modulator (RM) is Monte Carlo characterized with the RM equivalent circuit model. Inter-die statistical distributions of Si-RM model parameters are determined from simple RM optical transmission and electrical reflection coefficient measurement, and the correlated model parameter sets are randomly generated for Monte Carlo simulation of 40-Gbps 4-level pulse AM (PAM-4) eye diagrams within simulation program with IC emphasis. From the resulting Monte Carlo simulated eye diagrams, the yield for the Si RMs that satisfy optical modulation amplitude and the ratio of level mismatch requirements can be corroborated with measurement. With these, the eye diagrams of Si electronic-photonic integrated PAM-4 transmitters with RMs and driver electronics are Monte Carlo characterized. This approach allows the extension of the standard Si IC characterization technique to the electronic-photonic ICs and can produce better-performing solutions with better yields in the design stage. [ABSTRACT FROM AUTHOR]

In applications whose databases have millions of rows, caching is essential to speed up the server response. The paper focuses on a new approach to testing the cache systems in the .NET 6 framework. In this paper, a system is created that uses Redis, MongoDB and SQL Server and an in-memory database as cache stores to evaluate their performance and scalability. A performance comparison of these cache systems provides detailed insights into the best practices for designing and implementing them in .NET 6 development environment. The results of this paper may be useful to developers working on similar projects to those who want to implement a caching system. [ABSTRACT FROM AUTHOR]

Nowadays, due to advancements in power electronic devices as well as the rise in consumer awareness of the need to protect the environment on a global scale, many people are turning to the use of solar photovoltaic (PV) technology in the distributed power generation side. In the field of power electronics, manufacturers need to develop products that have high lifespans. Power electronic device reliability is important for the maintenance of the device and may be scheduled under that information. Rather than preventing failures, reliability can be improved by predicting them. Even though some research has been conducted over the past few years to investigate the reliability of power electronic devices, the reliability is many common circuits has not been investigated and this leads to a big challenge for researchers. In this review paper, an overview of the grid-connected multilevel inverters for PV systems with motivational factors, features, assessment parameters, topologies, modulation schemes of the multilevel inverter, and the selection process for specific applications are presented. In this paper, the findings of a comprehensive reliability analysis of fundamental multilevel inverters are studied. To evaluate the reliability of three basic multilevel inverters, a calculation is made using each component's mean time before its failure. Two techniques of computation approximate and exact were used to arrive at the final result. To calculate power losses in temperature-sensitive components such as diodes and switches, MATLAB Simulink is employed. In addition, the concept of oversizing photovoltaic (PV) arrays is presented in this study. This concept proposes that energy output may be increased by increasing the size of the PV array under conditions of poor solar irradiation. Finally, the mission-profile-based and Monte Carlo simulation-based methods process flows are discussed for the accurate lifetime prediction and reliability assessments of PV inverters in a real-time scenario, followed by a conclusion with future work. [ABSTRACT FROM AUTHOR]

The present paper provides an environmental assessment and ranking of different treatment options for the organic fraction of municipal solid waste (OFMSW), which is a biowaste that typically contains food- and green-waste. The main biochemical treatment systems for OFMSW are composting (by-product: fertilizer) and anaerobic digestion (by-products: biogas and digestate), which are often combined in practice. Total impact scores as evaluated by means of Life Cycle Assessment (LCA) with the Ecological Scarcity Method range from 8 to 31 eco-points for Germany (EPG) per kg treated OFMSW with “Global Warming” and “Main Air Pollutants” (such as NH3) as main environmental impacts. In spite of significant uncertainties in the available emission data, the subsequent application of a Monte Carlo Analysis provides a robust ranking of the treatment systems. The analysis reveals that the transportation distance is a crucial factor to increase the ecological benefit of an OFMSW treatment system. Consequently, decentral structures with short transportation distances (e.g. 17 km) as well as an optimal plant operation mode are more important to reduce emissions than the choice of the treatment system itself. Further research should focus on monitoring campaigns to generate better representative operational datasets for the different types of OFMSW treatment plants such as plug-flow or batch digestion systems as well as for the composting technologies.

Exploring an efficient research method for understanding color preference is important to researchers and designers. This work compares four experimental methods for individual color preference research (N‐alternative forced choice, rank‐order, rating and paired comparison). Three psychophysical experiments were carried out with 338 participants. Participants were presented with six color patches (red, orange, yellow, green, blue and purple) arranged in a random order. This work suggested orange is the strongest preferred color and green is the weakest preferred using three individual color preference experimental methods with six hues. The Monte Carlo Analysis method further compares the result performance for four methods, which suggests the rating, paired comparison and rank‐order methods are more stable than the N‐alternative forced choice method when only a small number of participants take part in the experiment. For studies involving small numbers of participants (even less than 6), the rating, rank‐order and pair comparison methods should be preferred. [ABSTRACT FROM AUTHOR]

Due to the continuous scaling of MOSFET (Metal Oxide Semiconductor Field-Effect Transistor) devices over the past few decades, power consumption has increased tremendously. To reduce power dissipation at lower technology nodes, digital logic circuits are designed with modern (FinFET) devices. In this paper, FinFET INDEP (input dependent) technique-based short gate (SG) FinFET Adder circuits are proposed at 10 nm technology node. The performance comparison of INDEP technique-based adder circuits is done with the SG FinFET adder circuits. The analysis of adder circuits is performed first in terms of functional verification (transient characteristics) and finally for different performance parameters such as propagation delay, power dissipation and power delay product (PDP). The proposed FinFET INDEP technique proves as one of the best leakage reduction techniques for FinFET adder circuits at lower technology nodes. To test the reliability of the circuits, Monte Carlo analysis is also performed. The PDP is improved by 16.8% and 13.73% in INDEP SG FinFET half adder(HA) and INDEP SG FinFET full adder(FA) at 10 nm technology, respectively, in comparison with the ones without INDEP technique. The Monte Carlo simulation results with 3σ Gaussian distribution at ±10% process, voltage and temperature variations show the improvement in PDP in case of SG INDEP FinFET FA and SG INDEP FinFET HA circuit in comparison to SG FinFET FA and FinFET HA circuit, respectively. Simulation is performed using HSPICE tool at 10 nm process technology node. [ABSTRACT FROM AUTHOR]

The current deployment of 5G NR in the frequency band 4800-4990 MHz in multiple countries near the coastlines indicated that there might be a potential risk of harmful interference impacting aeronautical and maritime systems located in international airspace and international waters. This raised numerous concerns about whether 5G NR system rollouts in that band need to be restricted by the power flux density limits created at the border of the territorial waters, which equals 12 nautical miles from the coastline. This work contains a case study based on the example of the Pacific region, where a simulation of aggregate interference from 5G NR base stations and user equipment deployed in the cities near the coastline using Monte Carlo analysis was conducted. The results of the study show that no harmful interference to the aeronautical and maritime services operating in international airspace and waters is expected even when the aircraft or vessels are located at the border of the territorial airspace and waters from the coastline. Therefore, no restriction to the 5G NR deployment in the coastline regions in the frequency band 4800-4990 MHz is required. [ABSTRACT FROM AUTHOR]

Rats produce ultrasonic vocalisation (USVs) that are classified into different types, based on their average frequency. In pups 40 kHz USVs are produced upon social isolation, and in adults USVs can be associated with affective states and specific behavioural patterns (i.e., appetitive 50 kHz vocalisations of frequency range 30-100 kHz, or aversive 20 kHz vocalisations of frequency range 18-30 kHz). Generally, USVs of frequency around 50 kHz are linked to activation of brain reward pathways, during anticipation or experience of rewarding stimuli. Previous studies have described several subtypes of 50 kHz USVs, according to their acoustic properties. We asked whether USV production might be relevant to feeding behaviour. We recorded USVs from 14-week old adult rats during the satisfaction of a physiological need: refeeding following mild food deprivation (17 h overnight fast). We analysed a 10 min consummatory phase, preceded by a 10 min anticipatory phase, as a control for the experimental meal. Following identification of USV subtypes, we applied frequentist and Bayesian (Monte Carlo shuffling) statistical analyses to investigate the relationship between USV emission and rat behaviour. We found that it was not total USV quantity that varied in response to food consumption, but the subtype of USV produced. Most importantly we found that rats who feed tend to produce flat USVs of a frequency around 40 kHz. Beyond the previous reports of circumstantial association feeding-flat USVs, our observation directly correlate vocalisation and ingestive behaviour. Our study highlights that, in addition to quantification of the production rate, study of USV subtypes might inform us further on rat consummatory behaviour. Since this vocalisation behaviour can have a communicative purpose, those findings also illustrate nutrition studies might benefit from considering the possible social dimension of feeding behaviour. [ABSTRACT FROM AUTHOR]

The Current Mirror (CM) technique is widely used in mixed-mode and analog integrated circuits for tasks such as current amplification, biasing, and active loading. The overall effectiveness of these circuits relies heavily on their efficient designs. Current mirrors are primarily employed to accurately replicate currents in a circuit, offering high stability, simplicity, and scalability. They have become indispensable building blocks in analog and mixed-signal circuits, with their significance growing along with the demand for high-performance and low-power designs. Numerous techniques have been proposed to improve the performance metrics of current mirrors, including accuracy, input resistance, output resistance, and bandwidth. This study compares the advantages and disadvantages of these different current mirror techniques on a unified platform. It includes a comprehensive analysis of various contemporary mirror topologies, and classifies them based on their distinct characteristics. The performances of different current mirrors, including the basic CM, Wilson CM, cascode CM, and folded cascode CM circuits, were thoroughly examined in this analysis. The objective of this study is to select an appropriate current mirror for specific applications. The circuits considered in this study accurately mirror a current of 100 µA with a ±2% error using the Cadence Virtuoso software and UMC 65 nm technology. Process, Voltage, and Temperature (PVT) analysis, along with Monte Carlo simulations, were conducted under similar conditions using a supply voltage of 1.2V to ensure a fair comparison across the various current mirror approaches. [ABSTRACT FROM AUTHOR]

Abstract Component damage and failure in sensor or actuator will cause system faults, resulting in reduced or lost performance. This topic has become an interesting and challenging issue that if we know the effect of faults on variables, control schemes can be designed to reduce the effect of faults on the system. Therefore, the quantification of the effect of the faults is very valuable in improving the performance of wind turbines. In this paper, the effect of some important faults is investigated in the three parts: rotor, drive, and power on the output power and the measured variables of wind turbines in the partial and full load regions using the Monte Carlo method. Then, the severity of these faults on the output power is ranked in the two regions by importance factor (IF). Also, due to the fact that some faults cause structural stress due to severe changes in the angle of the blades or their asymmetry, so the stresses caused by faults are discussed. The results show that these faults severity on the output power and the measured variables of wind turbines is different in the two regions. Our conclusion provides an opportunity for wind power plant operators and investors to improve plant performance and scheduled repairs by knowing the effect of faults on wind turbine variables. Knowing effect of the faults or the severity of each of them can increase the operating time of the wind turbine and reduce costs.

• An SCW-SMR core model is developed based on Serpent 2 simulations. • Assembly structures and materials are studied to decrease neutron absorption. • Effects of moderator temperature and assembly gap size changes are examined. • Enrichment maps are tested to increase reserve reactivity and shape power profiles. • Resulting core model has adequate burnup cycle length and power profiles. Serpent 2 particle transport code is used to develop the pre-conceptual neutronic design of the Supercritical Water Cooled SMR. After initial criticality and burnup calculations, the starting core design of (Schulenberg and Otic, 2021) is improved using predetermined criteria, such as burnup cycle length and power distribution, while also considering operational safety. In order to achieve higher reserve reactivity, several modifications are considered, including the introduction of alternative structural materials and fuel assembly wall type, moderation improvement by adjustment of moderator temperature and fuel assembly gap width, and selection of a suitable enrichment map. As a result of the introduced modifications, the burnup cycle length is increased to 26 months and an acceptable core power distribution is achieved. The improved core design can be used for further investigations, such as coupled calculations using neutronic and thermal–hydraulic codes and examinations targeting reactivity control during burnup. [ABSTRACT FROM AUTHOR]

• Life cycle assessment of energy supply contracted heat supply systems. • Both embodied and operational impacts are included for 18 impact indicators. • Systems operated on the basis of energy supply contracting lead to lower impacts. • This is due to the efficiency of the system, which is about 16% higher. • Efficiency is found to be the most influential parameter of the system. Heat supply systems (HSS) have the particularity that their energy-related services can be outsourced to a third party or contractor, which is usually referred to as energy supply contracting (ESC). Although the economics of ESC have been extensively researched, life cycle assessments of HSS with ESC are rather rare. The aim of this study is to assess the environmental impacts of an HSS operated in Austria, from cradle to grave. The measured energy consumption is used to assess the operational impacts, thus eliminating the need for calculation assumptions regarding efficiency and heat demand. In addition, the trade-off from using more efficient components in HSS, which possibly leads to higher embodied emissions prior to commissioning, is explored. Overall, our results suggest that systems operating with an ESC display better environmental performance, assuming an efficiency difference to conventional HSS of around 16%, even if this leads to higher embodied impacts. To support these conclusions, the next step would be to model these systems in dedicated software. This would also provide a further opportunity to investigate options for further improvements to the systems under consideration. [ABSTRACT FROM AUTHOR]

Residential consumers play an important role in the sustainable transition of the energy system by leveraging their household loads for demand response (DR). This paper aims to analyze the enrollment rates of residential consumers within DR through an agent-based model (ABM). Both economic and noneconomic (social/behavioral) parameters that influence the consumer enrollment in DR are considered. An energy management model, a home energy management system (HEMS), is used to identify the potential economic savings of consumers enrolling in DR. Consumers are randomly assigned to different neighborhoods and have different social relationships (e.g., friends, neighbors), which, in turn, influences their decision-making in the ABM. The results of this paper highlight the indirect relationship of expected annual savings and direct relationship of the share of consumers having electric vehicles (EV), photovoltaics (PV), and battery energy storage systems (BESSs) on the DR enrollment rates. Based on the enrollment rates, the maximum energy savings were obtained in April and the minimum during the last quarter of the year. Monte Carlo analysis is employed to handle the randomness associated with different variable selections, which provides a ± 10 % variation of consumer enrollment rate in DR. The results of this study have practical implications for energy flexibility in the residential sector. • Introduced an agent-based model to simulate residential consumer enrollment in DR. • Utilized economic and noneconomic factors to identify consumer decision-making to enroll. • Introduced different enrollment contract types in DR for consumers. • Analyzed different parameters influencing consumer enrollment rates. [ABSTRACT FROM AUTHOR]

• Establish a Monte Carlo improved simulation model considering the particle size of underwater transmission media. • The improved Monte Carlo simulation method for fitting phase functions through random sampling provides a more comprehensive and accurate complex water transport model. • The improved simulation model combine the scattering angle and the scattering phase function which make it is more in line with the actual probability model of complex water environment. • Obtained the influence of different variables on the polarization maintaining performance of polarized light. The information about the polarization of underwater objects can be affected by the absorption and scattering of water particles, making it challenging to detect underwater targets accurately. Therefore, it is essential to analyze the characteristics of polarization transmission in water. Traditional Monte Carlo simulations have yet to effectively treat particle size in water, which is unsuitable for the underwater environment of polydispersity particles with significant particle size differences. In this paper, a new simulation model using a Monte Carlo method with random sampling fitting phase functions is proposed, which makes the transmission characteristics of water particles more in line with the actual probability model of complex water bodies. The experimental results demonstrate that the proposed Monte Carlo method produces polarization closer to experimental results. The larger the particle size of water suspensions, the greater change of the polarization degree of polarized light. The polarization-maintaining characteristics of circularly polarized light are better than those of linearly polarized light, providing data support for the transmission and detection of underwater light. [ABSTRACT FROM AUTHOR]

Enhancing rural livelihoods in low to medium-income countries through innovative agricultural technologies is a critical challenge for decision-makers. Cost-effective interventions like essential oil extraction (EOE) technology for aromatic plants need rural adoption. The study assesses two EOE practices' economic benefits in Punjab, Pakistan, using three models: individual benefit-cost (BC), diffusion, and a Pothwar-specific BC model. Thus, analyzing results from the literature, expert insights, and indigenous knowledge can readily be employed in scenarios where data is limited in less developed economies, including Pakistan. The study findings revealed monetary costs and financial returns at both individual and zonal levels. The highest positive NPV value was recorded in the case of mint oil (267.86) followed by eucalyptus oil and wood (755.12) productivity for short-term and long-term benefits respectively. In addition, the maximum BC index (4.03) was recorded under eucalyptus oil and wood, followed by mint essential oil (3.82) production for 10 years. The model(s) further explored the key input parameters that positively impact the economic gains of the interventions and for ongoing future investments. Hence, the general application of the existing framework is also discussed, along with the limitations under different scenarios. • EOE interventions introduced as cost-effective strategy among rural masses. • Triple BC models analyzed with computational tools, simulative modeling, and risk evaluation. • Eucalyptus and mint oils economic viability over conventional methods. • Transitioning to EOE practices offers adopters advantage. • EOE interventions yielded optimal results for future investments. [ABSTRACT FROM AUTHOR]

This work presents an estimate of the slip activation potential of existing fractures in a remote northern community located on Canadian Shield rocks for geothermal purposes. To accomplish this objective, we analyzed outcrop analogues and recorded geometrical properties of fractures, namely the strike and dip. Then, we estimated the stress regime in the study area through an empirical approach and performed a probabilistic slip tendency analysis. This allowed us to determine the slip probability of the pre-existing fractures at the current state of stress, the orientation of fractures that are most likely to be activated and the fluid pressures needed for the slip activation of pre-existing fractures, which are key aspects for developing Enhanced Geothermal Systems. The results of this simple, yet effective, analysis suggest that at the current state of stress, the pre-existing natural fractures are relatively stable, and an injection pressure of about 12.5 MPa/km could be required to activate the most optimally oriented fractures to slip. An injection of water at this pressure gradient could open the optimally oriented pre-existing fractures and enhance the permeability of the reservoir for geothermal fluid extraction. The information described in this paper provides a significant contribution to the geothermal research underway in remote northern communities.

Measurement and response decoding is an ongoing challenge in the chipless radio-frequency identification (RFID) field. Measurement uncertainties, including tag/reader misalignment, S-parameter error, and clutter, can cause response distortions, such as magnitude changes and resonant frequency shifts, that can lead to the improper assignment of a binary code or sensing parameter (i.e., decoding). This work aims to use local sensitivity analysis and Monte Carlo simulation to fully characterize the effects of misalignment, response parameter measurement error (e.g., VNA S-parameter error), and clutter on chipless RFID responses that are measured in the near-field with a monostatic setup. From this type of comprehensive characterization, conclusions are drawn about the identification (ID) and sensing capabilities of the tags. While the effect of misalignment-based uncertainty was examined in Part I, here in Part II, $S_{11}$ uncertainty and clutter-based uncertainty are examined both individually and in combination with misalignment-based uncertainty. An example, demonstrating the application of the proposed tag performance assessment framework is also provided.

Measurement and response decoding is an ongoing challenge in the chipless radio-frequency identification (RFID) field. Measurement uncertainties, including tag/reader misalignment, radar cross-section or S-parameter error, and clutter, can cause response distortions, such as magnitude changes and resonant frequency shifts. These response distortions can lead to the improper assignment of a binary code or sensing parameter (i.e., improper decoding). This work aims to use local sensitivity analysis and Monte Carlo simulation to fully characterize the effects of misalignment, response parameter measurement error (e.g., vector network analyzer S-parameter error), and clutter on chipless RFID tag responses. From this type of comprehensive characterization, conclusions are drawn about the identification (ID) and sensing capabilities of the tags. In this work, the simulations are performed for two specific tags and the results are then corroborated with measurements of one of the tags. While the work is done for a near-field monostatic measurement setup, it is presented such that the same procedures can be applied to other tags and measurement setups, including far-field scenarios. Thus, a novel comprehensive tag performance assessment framework is provided. This work is divided into two parts. In Part I, the effects of tag/reader misalignment uncertainty are examined in depth through both simulations and measurements. In Part II, the effects of S-parameter error, clutter-based uncertainty, and the combination of these uncertainties with misalignment uncertainty are investigated. An example demonstrating the application of this tag performance assessment framework is also provided in Part II.

Rats produce ultrasonic vocalisation (USVs) that are classified into different types, based on their average frequency. In pups 40 kHz USVs are produced upon social isolation, and in adults USVs can be associated with affective states and specific behavioural patterns (i.e., appetitive 50 kHz vocalisations of frequency range 30−100 kHz, or aversive 20 kHz vocalisations of frequency range 18−30 kHz). Generally, USVs of frequency around 50 kHz are linked to activation of brain reward pathways, during anticipation or experience of rewarding stimuli. Previous studies have described several subtypes of 50 kHz USVs, according to their acoustic properties. We asked whether USV production might be relevant to feeding behaviour. We recorded USVs from 14-week old adult rats during the satisfaction of a physiological need: refeeding following mild food deprivation (17 h overnight fast). We analysed a 10 min consummatory phase, preceded by a 10 min anticipatory phase, as a control for the experimental meal. Following identification of USV subtypes, we applied frequentist and Bayesian (Monte Carlo shuffling) statistical analyses to investigate the relationship between USV emission and rat behaviour. We found that it was not total USV quantity that varied in response to food consumption, but the subtype of USV produced. Most importantly we found that rats who feed tend to produce flat USVs of a frequency around 40 kHz. Beyond the previous reports of circumstantial association feeding-flat USVs, our observation directly correlate vocalisation and ingestive behaviour. Our study highlights that, in addition to quantification of the production rate, study of USV subtypes might inform us further on rat consummatory behaviour. Since this vocalisation behaviour can have a communicative purpose, those findings also illustrate nutrition studies might benefit from considering the possible social dimension of feeding behaviour.

Heavy metal pollution is a major concern in China because of its serious effects on human health. To assess potential human health and ecological risks of heavy metal pollution, concentration data for seven heavy metals (As, Pb, Cd, Cr, Hg, Cu, Zn) from 14 sites spanning the rural-urban interface of the Wen-Rui Tang River watershed in southeast China were collected from 2000 to 2010. The heavy metal pollution index (HPI), hazard index (HI) and carcinogenic risk (CR) metrics were used to assess potential heavy metal risks. Further, we evaluated the uncertainty associated with the risk assessment indices using Monte Carlo analysis. Results indicated that all HPI values were lower than the critical level of 100 suggesting that heavy metal levels posed acceptable ecological risks; however, one site having an industrial point-source input reached levels of 80-97 on several occasions. Heavy metal concentrations fluctuated over time, and the decrease after 2007 is due to increased wastewater collection. The HI suggested low non-carcinogenic risk throughout the study period (HI  10-4). While most metrics for human health risk did not exceed critical values for heavy metals, there is still a potential human health risk from chronic exposure to low heavy metal concentrations due to long-term exposure and potential metal interactions. Results of this study inform water pollution remediation and management efforts designed to protect public health in polluted urban area waterways common in rapidly developing regions.